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<div id="header">
<h1 class="title toc-ignore">Locating KBAs: An automated workflow for
identifying potential Key Biodiversity Areas</h1>
<h4 class="author">Daniela Linero - National Audubon Society</h4>
</div>
<div id="TOC">
<ul>
<li><a href="#introduction">Introduction</a></li>
<li><a href="#methodology">Methodology</a>
<ul>
<li><a href="#installation-and-initial-requirements">1. Installation and
initial requirements</a></li>
<li><a href="#workflow">2. Workflow</a></li>
<li><a href="#detailed-step-by-step-instructions">3. Detailed
step-by-step instructions</a></li>
</ul></li>
<li><a href="#example-outputs">Example outputs</a></li>
<li><a href="#howto">How to run the workflow code in your local
computer</a></li>
<li><a href="#additional-resources">Additional resources</a></li>
<li><a href="#citation">Citation</a></li>
<li><a href="#contact">Contact</a></li>
<li><a href="#references">References</a></li>
</ul>
</div>
<div id="introduction" class="section level3">
<h3>Introduction</h3>
<hr />
<p>In the face of an alarming and accelerating loss of biodiversity, it
is essential to safeguard the places that contribute significantly to
the persistence of species around the world. The IUCN Species Survival
and World Protected Areas Commissions recently led an effort to develop
a <a
href="https://portals.iucn.org/library/sites/library/files/documents/2016-048.pdf">standard</a>
for identifying the places with the highest conservation value, the Key
Biodiversity Areas (KBAs; IUCN, 2016). In the process of identifying
KBAs, it is recommended to first conduct a comprehensive scoping
analysis (KBA Standards and Appeals Committee, 2020). However, this
analysis requires a great effort to obtain, compile and analyze spatial
data for as many taxonomic groups as possible. The <em>Locating KBAs
workflow</em> helps to streamline the scoping analysis by using the R
programming language and leveraging GBIF data. The workflow code
accesses the occurrence data of species present in a user-defined area
and determines all those that could trigger the criteria of the KBA
standard. Subsequently, it helps users identifying the places where the
potential trigger species occur in significant numbers. In this way, the
workflow enables users to efficiently and transparently identify the
sites where it is most appropriate to focus efforts on gathering
information on mature individuals, engaging stakeholders, and applying
the standard’s criteria.</p>
<style>
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<p><strong>On this website you can find an overview of the workflow and
the requirements and steps necessary to run the code. Click on the
Notebook tab to see the workflow code and interact with the main
results, such as tables and maps. Click on the GitHub repository tab to
go to the repository where the script is stored. You can clone the
script on your computer to modify and run it locally (see section <a
href="#howto">How to run the workflow code in your local
computer</a>).</strong></p>
</div>
</div>
<div id="methodology" class="section level3">
<h3>Methodology</h3>
<hr />
<div id="installation-and-initial-requirements" class="section level4">
<h4>1. Installation and initial requirements</h4>
<p>To get started, you need to confirm that you have the following
requirements:</p>
<ul>
<li><p>Have R and RStudio installed on your computer. If you do not have
them, please download and install <a
href="https://cran.r-project.org/">R</a> first and continue downloading
and installing <a
href="https://www.rstudio.com/products/rstudio/">RStudio</a>.</p></li>
<li><p>Have a GitHub account and GitHub Desktop installed on your
computer. You can create a free GitHub account <a
href="https://github.com/">here</a> and download GitHub Desktop <a
href="https://desktop.github.com/">here</a>.</p></li>
<li><p>Have a GBIF account. If you do not have one yet, create it using
this <a href="https://www.gbif.org/user/profile">link</a>.</p></li>
<li><p>Request an API token <a
href="https://apiv3.iucnredlist.org/">here</a> to access the IUCN Red
List information.</p></li>
<li><p>In case you want to assess bird species, request a copy of the
dataset of global bird distributions from Birdlife International <a
href="http://datazone.birdlife.org/species/requestdis">here</a> (this
may take several days).</p></li>
</ul>
<p>Once you have met all the above requirements, open RStudio and make
sure you have the following packages installed; otherwise use the
following code to install them:</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="fu">install.packages</span>(<span class="fu">c</span>(<span class="st">"tidyverse"</span>, <span class="st">"Hmisc"</span>, <span class="st">"rgbif"</span>, <span class="st">"wellknown"</span>, <span class="st">"rredlist"</span>, <span class="st">"ggplot2"</span>, <span class="st">"ggspatial"</span>, <span class="st">"RCurl"</span>, “xml2”, “rvest”, “sf”, <span class="st">"sp"</span>, “DT”, “leaflet”, “knitr”, <span class="st">"foreach"</span>, <span class="st">"doSNOW"</span>, <span class="st">"parallel"</span>, <span class="st">"stringi"</span>, <span class="st">"CoordinateCleaner"</span>, <span class="st">"countrycode"</span>, <span class="st">"taxadb"</span>))</span></code></pre></div>
</div>
<div id="workflow" class="section level4">
<h4>2. Workflow</h4>
<p>The workflow code presented in the notebook tab, accessible through
the GitHub repository, is designed to facilitate and streamline the
scoping analysis for KBAs identification by leveraging the free and open
access data of GBIF. Before exploring and running the workflow code, I
encourage users to familiarize themselves with the <a
href="https://portals.iucn.org/library/sites/library/files/documents/2016-048.pdf">Global
Standard for the Identification of Key Biodiversity Areas</a> (IUCN,
2016) and the <a
href="https://portals.iucn.org/library/sites/library/files/documents/2020-033-En.pdf">Guidelines
for using this standard</a> (KBA Standards and Appeals Committee,
2020).</p>
<p>In this workflow, we will focus solely on the following species-based
criteria:</p>
<ul>
<li>A1 for globally threatened species</li>
<li>B for restricted-range species</li>
<li>D1 for congregations during a particular stage of the life
cycle</li>
</ul>
<p>The workflow is divided into <strong>three main steps</strong>.
First, the user downloads and cleans GBIF occurrence data. The code then
retrieves information for each species present in the dataset, accessing
the IUCN Red List and Bird Data Zone portals and the tools provided in
the following KBA <a
href="http://www.keybiodiversityareas.org/working-with-kbas/proposing-updating/criteria-tools">webpage</a>.
With this information, the code <strong>selects the species present in
the study area that have the potential to trigger the aforementioned KBA
criteria.</strong> The second step is to apply two functions that allow
the user to map the location of the potential trigger species and
<strong>identify the sites where they occur in significant
numbers.</strong> In the case of bird species, it is also possible to
locate the places where they meet the thresholds of the KBA criteria
considered. The last step of the workflow is to <strong>obtain the
citations</strong> of the different sources of information consulted in
the previous steps.</p>
<p>The scheme below represents the overall workflow</p>
<div class="figure" style="text-align: center">
<img src="methods/Workflow.jpeg" alt="Fig 1. Scheme representing the main steps of the Locating KBAs workflow" width="80%" />
<p class="caption">
Fig 1. Scheme representing the main steps of the Locating KBAs workflow
</p>
</div>
</div>
<div id="detailed-step-by-step-instructions" class="section level4">
<h4>3. Detailed step-by-step instructions</h4>
<p>In the Notebook tab you will find the explanation of all the steps
needed to complete the workflow and their associated code. Additionally,
you will be able to interact with the most important results of the
workflow, such as the table of potential trigger species and the maps of
the sites where they occur in significant numbers.</p>
</div>
</div>
<div id="example-outputs" class="section level3">
<h3>Example outputs</h3>
<hr />
<p>The following is a preview of the table to identify potential trigger
species under KBA criteria (globally threatened species, restricted
range species, species that form seasonal congregations). For bird
species, it is also possible to obtain the global number of mature
individuals and calculate the criteria thresholds.</p>
<center>
<img src="https://media.giphy.com/media/DWLQNMalkuxhvMXRbG/giphy.gif"
width="600" />
</center>
<p>The script also contains a function that will help the user
identifying the sites where potential trigger species have large counts
or where there are multiple records of potential trigger species.</p>
<center>
<img src="https://media.giphy.com/media/oWrsaglCvK79HCkV82/giphy.gif"
width="500" />
<center>
<p>A second function, available only for bird species, creates an
interactive map showing the location of records that meet the threshold
of individuals for each criterion evaluated.</p>
<center>
<img src="https://media.giphy.com/media/n7im3EPT7aMvoEBgr7/giphy.gif"
width="500" />
<center>
</div>
<div id="howto" class="section level3">
<h3>How to run the workflow code in your local computer</h3>
<hr />
<ol style="list-style-type: decimal">
<li><p>Sign in into your GitHub account <a
href="https://github.com/">here</a>.</p></li>
<li><p>To copy the repository to your profile, go to the search tab at
the top of the screen and type
dLinero-KBAs/dlinero-KBAs.github.io</p></li>
</ol>
<p><img src="methods/howto_step1.jpg" width="75%" style="display: block; margin: auto;" /></p>
<ol start="4" style="list-style-type: decimal">
<li><p>Click on the repository</p></li>
<li><p>Click the fork button in the right corner.</p></li>
</ol>
<p><img src="methods/howto_step5.jpg" width="75%" style="display: block; margin: auto;" /></p>
<ol start="6" style="list-style-type: decimal">
<li><p>If you want to open or modify the files and run the code in your
local computer, open the GitHub Desktop software.</p></li>
<li><p>If this is your first time opening the software, it will ask you
to sign into your GitHub account. Once done, select the Locating KBAs
repository and click the clone button at the bottom.</p></li>
</ol>
<p><img src="methods/howto_step7.jpg" width="75%" style="display: block; margin: auto;" /></p>
<ol start="8" style="list-style-type: decimal">
<li>In the pop-up window, select GitHub.com and set the folder where you
want to save all the files that are in the repository.</li>
</ol>
<p><img src="methods/howto_step8.jpg" width="75%" style="display: block; margin: auto;" /></p>
<ol start="9" style="list-style-type: decimal">
<li><p>Select clone</p></li>
<li><p>After GitHub desktop finishes cloning the files to your local
computer, select show in explorer to open the folder where the files
were saved.</p></li>
</ol>
<p><img src="methods/howto_step10.jpg" width="75%" style="display: block; margin: auto;" /></p>
<ol start="11" style="list-style-type: decimal">
<li>Open the dlinero-KBAs.github.io RStudio project. In the lower right
corner, select Notebook.Rmd to open the Rmarkdown file.</li>
</ol>
<p><img src="methods/howto_step11.jpg" width="75%" style="display: block; margin: auto;" /></p>
<ol start="12" style="list-style-type: decimal">
<li>Now you are ready to modify the script and run it!</li>
</ol>
</div>
<div id="additional-resources" class="section level3">
<h3>Additional resources</h3>
<hr />
<p>Introductory video: <a
href="https://youtu.be/oesnhDeYpHQ">https://youtu.be/oesnhDeYpHQ</a></p>
</div>
<div id="citation" class="section level3">
<h3>Citation</h3>
<hr />
<p>Linero D (2021) Locating KBAs: An automated workflow for identifying
potential Key Biodiversity Areas. <a
href="https://github.com/dLinero-KBAs/dlinero-KBAs.github.io">https://github.com/dLinero-KBAs/dlinero-KBAs.github.io</a></p>
</div>
<div id="contact" class="section level3">
<h3>Contact</h3>
<hr />
<p>Feel free to email me at <a href="mailto:daniela.linero@audubon.org"
class="email">daniela.linero@audubon.org</a></p>
<p><a
href="https://www.researchgate.net/profile/Daniela-Linero">ResearchGate
profile</a></p>
<p><a href="https://www.linkedin.com/in/daniela-linero/">LinkedIn
profile</a></p>
</div>
<div id="references" class="section level3">
<h3>References</h3>
<hr />
<ul>
<li><p>Gueta, T., Carmel, Y (2016). Quantifying the value of user-level
data cleaning for big data: A case study using mammal distribution
models. Ecological Informatics, 34, 139-145. <a
href="https://doi.org/10.1016/j.ecoinf.2016.06.001"
class="uri">https://doi.org/10.1016/j.ecoinf.2016.06.001</a></p></li>
<li><p>IUCN (2016). A Global Standard for the Identification of Key
Biodiversity Areas, Version 1.0. First edition. Gland, Switzerland:
IUCN.</p></li>
<li><p>KBA Standards and Appeals Committee (2020). Guidelines for using
A Global Standard for the Identification of Key Biodiversity Areas.
Version 1.1. Prepared by the KBA Standards and Appeals Committee of the
IUCN Species Survival Commission and IUCN World Commission on Protected
Areas. Gland, Switzerland: IUCN. viii + 206 pp.</p></li>
</ul>
</div>
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